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一项关于疫情爆发一年后情绪反应的重复测量研究。

A repeated-measures study on emotional responses after a year in the pandemic.

作者信息

Mozes Maximilian, van der Vegt Isabelle, Kleinberg Bennett

机构信息

Dawes Centre for Future Crime, University College London, London, UK.

Department of Computer Science, University College London, London, UK.

出版信息

Sci Rep. 2021 Nov 30;11(1):23114. doi: 10.1038/s41598-021-02414-9.

Abstract

The introduction of COVID-19 lockdown measures and an outlook on return to normality are demanding societal changes. Among the most pressing questions is how individuals adjust to the pandemic. This paper examines the emotional responses to the pandemic in a repeated-measures design. Data (n = 1698) were collected in April 2020 (during strict lockdown measures) and in April 2021 (when vaccination programmes gained traction). We asked participants to report their emotions and express these in text data. Statistical tests revealed an average trend towards better adjustment to the pandemic. However, clustering analyses suggested a more complex heterogeneous pattern with a well-coping and a resigning subgroup of participants. Linguistic computational analyses uncovered that topics and n-gram frequencies shifted towards attention to the vaccination programme and away from general worrying. Implications for public mental health efforts in identifying people at heightened risk are discussed. The dataset is made publicly available.

摘要

新冠疫情封锁措施的实施以及恢复正常生活的展望对社会变革提出了要求。最紧迫的问题之一是个人如何适应这一疫情。本文采用重复测量设计研究了对疫情的情绪反应。于2020年4月(严格封锁措施期间)和2021年4月(疫苗接种计划开始取得成效时)收集了数据(n = 1698)。我们要求参与者报告他们的情绪,并在文本数据中表达出来。统计测试显示出人们对疫情的适应情况总体呈改善趋势。然而,聚类分析表明存在一种更为复杂的异质性模式,即有一个应对良好的参与者亚组和一个顺从的参与者亚组。语言计算分析发现,话题和词频分布转向了对疫苗接种计划的关注,而不再是普遍的担忧。文中讨论了在识别高风险人群方面对公共心理健康工作的启示。该数据集已公开提供。

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